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πŸš€ v1.0.0 - Release of Hungarian Network

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@MaloOLIVIER MaloOLIVIER released this 02 Jan 13:19
· 2 commits to master since this release

Release v1.0.0

We are excited to announce the first official release of the Hungarian Network (Hnet) repository! This initial version lays the foundation for multi-source localization (DoA estimation) using the deep learning-based Hungarian algorithm implementation. Below are the key features, functionalities, and components included in this release.

πŸ”‘ Key Features

1. Synthetic Data Generation

  • generate_hnet_training_data.py
    • Generates synthetic distance matrices and association matrices essential for training the Hnet model.
    • Supports various configurations for angular resolutions and DoA combinations.

2. Model Training

  • run.py
    • Main script to train the Hnet model using the generated datasets.
    • Utilizes PyTorch Lightning for streamlined training loops and Hydra for configuration management.

3. Configuration Management

  • configs/ Directory
    • Contains YAML configuration files.
    • Facilitates easy customization of training parameters, logging settings, and more.

4. Testing and Coverage

  • test.py
    • Comprehensive test suite to validate model functionality and performance.
  • pytest.ini
    • Configuration file for Pytest to manage test settings.
    • tests/ Directory : consistency and scenario tests are located in tests/ directory.
  • htmlcov/ Directory
    • Contains HTML coverage reports to monitor test coverage and identify untested code segments.

6. Continuous Integration (CI)

  • /.github/workflows/ci-cd.yml
    • GitHub Actions workflow file to automate testing, coverage checks, and Docker image builds upon commits and pull requests.